A mine electromechanical equipment fault diagnosis method

By generating a global equipment dependency dataset and a fault tracing knowledge table, combined with real-time monitoring data, the problems of unorganized global relationships and unutilized data in the fault diagnosis of mining electromechanical equipment were solved, realizing systematic fault tracing and risk assessment, and improving the accuracy and efficiency of diagnosis.

CN122242755APending Publication Date: 2026-06-19JIANGXI NUCLEAR IND CONSTR CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JIANGXI NUCLEAR IND CONSTR CO LTD
Filing Date
2026-03-23
Publication Date
2026-06-19

AI Technical Summary

⚠Technical Problem

In the diagnosis of faults in mining electromechanical equipment, there are problems such as the lack of overall equipment relationships, insufficient use of data, reliance on manual experience for diagnosis, unstable accuracy, difficulty in locating the root cause of the fault, and lack of clear risk assessment, which leads to waste of resources and safety hazards.

⚗Method used

Generate a global device dependency dataset, construct a fault tracing knowledge table based on historical operation and maintenance data, and output a systemic fault tracing map through a dual-path analysis mechanism combined with real-time status monitoring data to achieve accurate tracing and risk assessment.

🎯Benefits of technology

It enables precise tracing of systemic failures in mining machinery and equipment, improves the accuracy and efficiency of diagnosis, ensures the scientific nature of operation and maintenance decisions and the quantification of risks, and reduces the loss of key evidence and waste of resources.

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Abstract

This invention discloses a fault diagnosis method for mining electromechanical equipment, belonging to the field of fault diagnosis technology. The method includes acquiring the identity information of all electromechanical equipment in the mining production system and the rigid dependencies between equipment, generating a global equipment dependency dataset. In the global equipment dependency dataset, the identity information of each equipment is associated with a list of rigidly dependent upstream equipment. From the global equipment dependency dataset, the list of rigidly dependent upstream equipment associated with the identity information of the target equipment is queried, and this list is determined as the core set of equipment to be analyzed. This invention overcomes the limitations of traditional single-point investigation and experience-based reliance, achieving a transformation from isolated diagnosis to system diagnosis, and from experience-based judgment to data-driven diagnosis. It solves the technical problems of low tracing efficiency and inaccurate location in traditional diagnostic methods, ensuring the stable operation of the mining production system.
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